Classification of Disease-Treatment HML
Reddi Prasadu,Department of Computer Science and Engineering, KL University, Vaddeswaram, AP, 522502, India
E. Adinarayana,Department of ECE, SMCE, Guntur
Machine Learning (ML) executions can be found in numerous spaces for computerization and simply as of late has turned into a solid apparatus in the medicinal area as well. ML is imagined as an instrument by which machine based frameworks can be coordinated in the health awareness part so as to show signs of improvement, quicker and more productive restorative consideration. This experimental space of programmed learning drives the production of insightful and mechanized applications that helps human services personals to embrace undertakings, for example, therapeutic choice help, restorative imaging, protein- protein connection, extraction of medicinal information, and a general patient administration framework. This paper depicts a Hybrid ML-based technique that is melded with a SVM classifier in blend with Bag-of-Words Representation and NLP assignments for building an application that is equipped for recognizing and spreading health awareness data. In its primary structure it concentrates sentences from restorative data sources, for example, distributed therapeutic papers, patient case sheets that say maladies and medications, and recognizes semantic relations that exist between the ailments and medicines. This key methodology acquires solid conclusions that could be coordinated in an application to be utilized as a part of the therapeutic consideration space. A usage of the proposed methodology accepts the claim.
Healthcare, machine learning, natural language processing, SVM classifier.
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